Oscillatory behavior is ubiquitous in the nervous system, from central pattern generators controlling movement, breathing and other motor functions to oscillations in the hippocampus, the thalamus and other cortical regions. Widespread synchronized oscillations in the brain could be pathological, as in generalized epilepsy and motor diseases of the basal ganglia. It is therefore important to understand how networks generate oscillations and what controls the period and phase relations of the individual components. This proposal specifically aims to understand the role that synaptic dynamics, in particular time- and frequency- dependent changes in synaptic efficacy, play in the network output. Time-dependent variations in synaptic efficacy, such as facilitation and depression, are present in most synapses. To understand the role of synaptic dynamics in shaping network output, experimental and theoretical techniques are combined to analyze and model individual synapses. The models are used to study synaptic dynamics within the context of the functional network. The experiments are performed on a small neuronal network, the lobster pyloric circuit. Neurons in the pyloric circuit produce a rhythm that is characterized by periodic bursts of action potentials in three phases. Most, if not all, synapses in this network show depression. As in all neuronal circuits, synaptic currents in the pyloric network involve complex interactions between properties of postsynaptic neurons and the activity patterns of presynaptic neurons . Neuronal activity is recorded during an ongoing rhythm to make libraries of realistic waveforms. These realistic activity waveforms are used to control the membrane potential of presynaptic neurons and record and analyze the synaptic responses. Qualitative and computational models of synapses are constructed using these data. The computational models are use to substitute biological synapses with artificial synapses, using the dynamic clamp technique. This procedure permits the manipulation of strength and time course of each individual synapse in a controlled manner, without directly affecting the other components in the network. Using these methods, the role of synaptic dynamics in regulating the network frequency and the phasing of the network components is examined. In particular, the functional roles of synaptic depression are investigated. Insights gained from this study are applicable to other rhythmic networks that show activity-dependent changes in synaptic efficacy.